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advance knowledge and improve the human condition. Explore how we are tackling critical challenges at the forefront of biology and medicine, and shaping a healthier, more sustainable future for all. Learn
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crystal / thin film scattering measurements, exploiting developments in artificial intelligence and machine learning. We also invite candidates with interests in beamline automation and autonomy
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Genome Curation Assistant (Jarvis ): an AI system that combines modern machine learning approaches with large-scale biological data to automate genome curation by detecting, interpreting, and correcting
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practice-engaged research on how engineers learn, how engineering knowledge and identities are formed, how we assess and evaluate learning, and how educational systems can be designed and transformed
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modern machine learning approaches with large-scale biological data to automate genome curation by detecting, interpreting, and correcting structural errors, reducing manual effort from weeks to minutes
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world-class, mission-driven programs. Staff at the Lab teach undergraduate courses, advise graduate students, collect and disseminate world-famous digital resources on biodiversity, and engage with
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research on how engineers learn, how engineering knowledge and identities are formed, how we assess and evaluate learning, and how educational systems can be designed and transformed to support meaningful
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Statistical and/or machine learning approaches to weather prediction Risk assessment and catastrophe modeling High-performance computing and large dataset manipulation The position involves close collaboration
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modeling and risk assessment, and demonstrated experience in one or several of the following areas: Tropical cyclone dynamics and thermodynamics Statistical and/or machine learning approaches to weather
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Biology with both high-throughput experimental (proteomics and genomics) and integrative computational (network analysis and machine learning) methodologies, aiming to understand gene functions and their